Name Venue Year citations
AC-Band: A Combinatorial Bandit-Based Approach to Algorithm Configuration. AAAI 2023 0
On Second-Order Scoring Rules for Epistemic Uncertainty Quantification. ICML 2023 0
Quantifying aleatoric and epistemic uncertainty in machine learning: Are conditional entropy and mutual information appropriate measures? UAI 2023 0
Is the volume of a credal set a good measure for epistemic uncertainty? UAI 2023 0
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams. ECML/PKDD 2023 0
Rectifying Bias in Ordinal Observational Data Using Unimodal Label Smoothing. ECML/PKDD 2023 0
A Survey of Methods for Automated Algorithm Configuration (Extended Abstract). IJCAI 2023 0
On the Calibration of Probabilistic Classifier Sets. AISTATS 2023 0
Koopman Kernel Regression. NIPS/NeurIPS 2023 0
SHAP-IQ: Unified Approximation of any-order Shapley Interactions. NIPS/NeurIPS 2023 0
Memorization-Dilation: Modeling Neural Collapse Under Noise. ICLR 2023 0
Multi-armed bandits with censored consumption of resources. MLJ 2023 0
Algorithm selection on a meta level. MLJ 2023 0
Incremental permutation feature importance (iPFI): towards online explanations on data streams. MLJ 2023 0
Towards Green Automated Machine Learning: Status Quo and Future Directions. JAIR 2023 0
A flexible class of dependence-aware multi-label loss functions. MLJ 2022 0
Pitfalls of Epistemic Uncertainty Quantification through Loss Minimisation. NIPS/NeurIPS 2022 3
Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical Comparison. UAI 2022 2
Stochastic Contextual Dueling Bandits under Linear Stochastic Transitivity Models. ICML 2022 0
Set-valued prediction in hierarchical classification with constrained representation complexity. UAI 2022 0
A Survey of Methods for Automated Algorithm Configuration. JAIR 2022 7
Machine Learning for Online Algorithm Selection under Censored Feedback. AAAI 2022 0
A Prescriptive Machine Learning Approach for Assessing Goodwill in the Automotive Domain. ECML/PKDD 2022 0
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with Semi-bandit Feedback and Finite Budget. NIPS/NeurIPS 2022 0
How to measure uncertainty in uncertainty sampling for active learning. MLJ 2022 0
Algorithm Selection as Superset Learning: Constructing Algorithm Selectors from Imprecise Performance Data. PAKDD 2021 4
Identification of the Generalized Condorcet Winner in Multi-dueling Bandits. NIPS/NeurIPS 2021 1
Robust Regression for Monocular Depth Estimation. ACML 2021 0
From Label Smoothing to Label Relaxation. AAAI 2021 23
On the Identifiability of Hierarchical Decision Models. KR 2021 1
Testification of Condorcet Winners in dueling bandits. UAI 2021 1
Credal Self-Supervised Learning. NIPS/NeurIPS 2021 7
Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning. TPAMI 2021 10
AutoML for Multi-Label Classification: Overview and Empirical Evaluation. TPAMI 2021 16
Gradient-Based Label Binning in Multi-label Classification. ECML/PKDD 2021 2
Single Player Monte-Carlo Tree Search Based on the Plackett-Luce Model. AAAI 2021 1
Multilabel Classification with Partial Abstention: Bayes-Optimal Prediction under Label Independence. JAIR 2021 2
TSK-Streams: learning TSK fuzzy systems for regression on data streams. DMKD 2021 0
On testing transitivity in online preference learning. MLJ 2021 0
Monocular Depth Estimation via Listwise Ranking Using the Plackett-Luce Model. CVPR 2021 0
Efficient set-valued prediction in multi-class classification. DMKD 2021 0
Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods. MLJ 2021 0
Preference-based Online Learning with Dueling Bandits: A Survey. JMLR 2021 0
Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals. IJCAI 2020 6
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis. ACML 2020 8
A Novel Higher-order Weisfeiler-Lehman Graph Convolution. ACML 2020 8
Introduction to the special issue of the ECML PKDD 2020 journal track. DMKD 2020 0
Learning Gradient Boosted Multi-label Classification Rules. ECML/PKDD 2020 19
A Neural Network-Based Driver Gaze Classification System with Vehicle Signals. IJCNN 2020 5
Reliable Multilabel Classification: Prediction with Partial Abstention. AAAI 2020 0
Preselection Bandits. ICML 2020 0
Introduction to the special issue of the ECML PKDD 2020 journal track. MLJ 2020 0
Learning to Aggregate: Tackling the Aggregation/Disaggregation Problem for OWA. ACML 2019 1
A Reduction of Label Ranking to Multiclass Classification. ECML/PKDD 2019 2
Multi-target prediction: a unifying view on problems and methods. DMKD 2019 0
ML-Plan: Automated machine learning via hierarchical planning. MLJ 2018 1
Ranking Distributions based on Noisy Sorting. ICML 2018 3
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty. IJCAI 2018 18
On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis. MLJ 2018 0
Learning to Rank Based on Analogical Reasoning. AAAI 2018 0
Dyad ranking using Plackett-Luce models based on joint feature representations. MLJ 2018 0
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening. ICML 2017 15
Learning TSK Fuzzy Rules from Data Streams. ECML/PKDD 2017 3
Learning to Aggregate Using Uninorms. ECML/PKDD 2016 9
Consistency of Probabilistic Classifier Trees. ECML/PKDD 2016 18
Predicting the Electricity Consumption of Buildings: An Improved CBR Approach. ICCBR 2016 2
Extreme F-measure Maximization using Sparse Probability Estimates. ICML 2016 91
Weighted Rank Correlation: A Flexible Approach Based on Fuzzy Order Relations. ECML/PKDD 2015 7
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach. NIPS/NeurIPS 2015 72
Qualitative Multi-Armed Bandits: A Quantile-Based Approach. ICML 2015 45
Superset Learning Based on Generalized Loss Minimization. ECML/PKDD 2015 43
Case Base Maintenance in Preference-Based CBR. ICCBR 2015 5
Online F-Measure Optimization. NIPS/NeurIPS 2015 33
Dyad Ranking Using A Bilinear Plackett-Luce Model. ECML/PKDD 2015 15
Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm. MLJ 2014 0
The Choquet kernel for monotone data. ESANN 2014 2
Preference-Based Rank Elicitation using Statistical Models: The Case of Mallows. ICML 2014 59
Learning Solution Similarity in Preference-Based CBR. ICCBR 2014 10
PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences. AAAI 2014 23
Guest editors' introduction: special issue of the ECML/PKDD 2014 journal track. DMKD 2014 0
Guest Editors' introduction: special issue of the ECML/PKDD 2014 journal track. MLJ 2014 0
On the bayes-optimality of F-measure maximizers. JMLR 2014 0
Editorial: Preference learning and ranking. MLJ 2013 8
Preference-Based CBR: A Search-Based Problem Solving Framework. ICCBR 2013 8
Preference-Based CBR: General Ideas and Basic Principles. IJCAI 2013 4
Learning to Rank Lexical Substitutions. EMNLP 2013 21
Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization. ICML 2013 97
Top-k Selection based on Adaptive Sampling of Noisy Preferences. ICML 2013 68
Consistent Multilabel Ranking through Univariate Losses. ICML 2012 34
On label dependence and loss minimization in multi-label classification. MLJ 2012 291
Preference-based reinforcement learning: a formal framework and a policy iteration algorithm. MLJ 2012 107
An Analysis of Chaining in Multi-Label Classification. ECAI 2012 53
Label Ranking with Partial Abstention based on Thresholded Probabilistic Models. NIPS/NeurIPS 2012 41
Probability Estimation for Multi-class Classification Based on Label Ranking. ECML/PKDD 2012 6
Learning monotone nonlinear models using the Choquet integral. MLJ 2012 2
Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning. ECML/PKDD 2011 42
Preferences in AI: An overview. Artificial Intelligence 2011 204
Learning Monotone Nonlinear Models Using the Choquet Integral. ECML/PKDD 2011 118
Bipartite Ranking through Minimization of Univariate Loss. ICML 2011 84
Preference-Based CBR: First Steps toward a Methodological Framework. ICCBR 2011 20
An Exact Algorithm for F-Measure Maximization. NIPS/NeurIPS 2011 111
Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss. ECML/PKDD 2010 51
Graded Multilabel Classification: The Ordinal Case. ICML 2010 48
Label Ranking Methods based on the Plackett-Luce Model. ICML 2010 91
Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains. ICML 2010 467
Predicting Partial Orders: Ranking with Abstention. ECML/PKDD 2010 59
Binary Decomposition Methods for Multipartite Ranking. ECML/PKDD 2009 79
FURIA: an algorithm for unordered fuzzy rule induction. DMKD 2009 387
Decision tree and instance-based learning for label ranking. ICML 2009 139
Combining Instance-Based Learning and Logistic Regression for Multilabel Classification. ECML/PKDD 2009 423
Combining instance-based learning and logistic regression for multilabel classification. MLJ 2009 0
Label ranking by learning pairwise preferences. Artificial Intelligence 2008 533
Multilabel classification via calibrated label ranking. MLJ 2008 785
A Critical Analysis of Variants of the AUC. ECML/PKDD 2008 41
A critical analysis of variants of the AUC. MLJ 2008 0
On Pairwise Naive Bayes Classifiers. ECML/PKDD 2007 33
Case-Based Multilabel Ranking. IJCAI 2007 73
On Minimizing the Position Error in Label Ranking. ECML/PKDD 2007 15
An Efficient Algorithm for Instance-Based Learning on Data Streams. ICDM 2007 18
Label Ranking in Case-Based Reasoning. ICCBR 2007 11
A Unified Model for Multilabel Classification and Ranking. ECAI 2006 124
Case-Based Label Ranking. ECML/PKDD 2006 22
Hierarchical Classification by Expected Utility Maximization. ICDM 2006 4
A systematic approach to the assessment of fuzzy association rules. DMKD 2006 204
Cho-k-NN: A Method for Combining Interacting Pieces of Evidence in Case-Based Learning. IJCAI 2005 11
Instance-Based Prediction with Guaranteed Confidence. ECAI 2004 5
Possibilistic instance-based learning. Artificial Intelligence 2003 37
Pairwise Preference Learning and Ranking. ECML/PKDD 2003 235
A Fuzzy Approach to Flexible Case-based Querying: Methodology and Experimentation. KR 2002 13
On the Representation and Combination of Evidence in Instance-Based Learning. ECAI 2002 4
Association Rules for Expressing Gradual Dependencies. ECML/PKDD 2002 87
Possibilistic Induction in Decision-Tree Learning. ECML/PKDD 2002 34
Implication-Based Fuzzy Association Rules. ECML/PKDD 2001 60
Focusing Search by Using Problem Solving Experience. ECAI 2000 5
Similarity-based Inference as Evitential Reasoning. ECAI 2000 0
Toward a Probabilistic Formalization of Case-Based Inference. IJCAI 1999 31
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